code: def validate(fabric, model, val_dataloader):
      fabric.print("Validating ...")
      model.eval()
      losses = torch.zeros(len(val_dataloader))
      for k, batch in enumerate(val_dataloader):
          input, target = batch
          output = model(input, target)
          loss = F.nll_loss(output, target.view(-1))
          losses[k] = loss.item()
      out = losses.mean()
      model.train()
      return out
  
file_path: pytorch-lightning/examples/fabric/language_model/train.py
imports: import lightning
  import torch
  import torch.nn.functional
  from lightning.pytorch.demos import Transformer, WikiText2
  from torch.utils.data import DataLoader, random_split
label_desc: Use image node_id 4 for calling a global function with example usage: validate(fabric, model, val_dataloader) and returns: out